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Summary of 4_Default_NeuralNetwork
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Neural Network
- n_jobs: -1
- dense_1_size: 32
- dense_2_size: 16
- learning_rate: 0.05
- explain_level: 1
Validation
- validation_type: kfold
- k_folds: 5
- shuffle: True
Optimized metric
rmse
Training time
7.3 seconds
Metric details:
| Metric |
Score |
| MAE |
116.216 |
| MSE |
22823.9 |
| RMSE |
151.076 |
| R2 |
0.703061 |
| MAPE |
0.178454 |
Learning curves
Permutation-based Importance
True vs Predicted
Predicted vs Residuals
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Summary of Ensemble
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Ensemble structure
| Model |
Weight |
| 10_LightGBM |
1 |
| 14_CatBoost |
1 |
| 2_Default_Xgboost |
1 |
| 3_Default_CatBoost |
2 |
Metric details:
| Metric |
Score |
| MAE |
106.452 |
| MSE |
19371.2 |
| RMSE |
139.18 |
| R2 |
0.747981 |
| MAPE |
0.16745 |
Learning curves
True vs Predicted
Predicted vs Residuals
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Summary of 10_LightGBM
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LightGBM
- n_jobs: -1
- objective: regression
- num_leaves: 15
- learning_rate: 0.05
- feature_fraction: 0.8
- bagging_fraction: 0.5
- min_data_in_leaf: 50
- metric: rmse
- custom_eval_metric_name: None
- explain_level: 1
Validation
- validation_type: kfold
- k_folds: 5
- shuffle: True
Optimized metric
rmse
Training time
12.6 seconds
Metric details:
| Metric |
Score |
| MAE |
107.131 |
| MSE |
19646.6 |
| RMSE |
140.166 |
| R2 |
0.744398 |
| MAPE |
0.168613 |
Learning curves
Permutation-based Importance
True vs Predicted
Predicted vs Residuals
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Summary of 3_Default_CatBoost
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CatBoost
- n_jobs: -1
- learning_rate: 0.1
- depth: 6
- rsm: 1
- loss_function: RMSE
- eval_metric: RMSE
- explain_level: 1
Validation
- validation_type: kfold
- k_folds: 5
- shuffle: True
Optimized metric
rmse
Training time
13.6 seconds
Metric details:
| Metric |
Score |
| MAE |
107.074 |
| MSE |
19566.2 |
| RMSE |
139.879 |
| R2 |
0.745444 |
| MAPE |
0.167898 |
Learning curves
Permutation-based Importance
True vs Predicted
Predicted vs Residuals
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Summary of 2_Default_Xgboost
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Extreme Gradient Boosting (Xgboost)
- n_jobs: -1
- objective: reg:squarederror
- eta: 0.075
- max_depth: 6
- min_child_weight: 1
- subsample: 1.0
- colsample_bytree: 1.0
- eval_metric: rmse
- explain_level: 1
Validation
- validation_type: kfold
- k_folds: 5
- shuffle: True
Optimized metric
rmse
Training time
4.2 seconds
Metric details:
| Metric |
Score |
| MAE |
107.739 |
| MSE |
19833.8 |
| RMSE |
140.832 |
| R2 |
0.741962 |
| MAPE |
0.168699 |
Learning curves
Permutation-based Importance
True vs Predicted
Predicted vs Residuals
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Summary of 14_CatBoost
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CatBoost
- n_jobs: -1
- learning_rate: 0.05
- depth: 8
- rsm: 0.8
- loss_function: RMSE
- eval_metric: RMSE
- explain_level: 1
Validation
- validation_type: kfold
- k_folds: 5
- shuffle: True
Optimized metric
rmse
Training time
845.1 seconds
Metric details:
| Metric |
Score |
| MAE |
107.17 |
| MSE |
19586.7 |
| RMSE |
139.952 |
| R2 |
0.745177 |
| MAPE |
0.16823 |
Learning curves
Permutation-based Importance
True vs Predicted
Predicted vs Residuals
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Summary of 6_Xgboost
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Extreme Gradient Boosting (Xgboost)
- n_jobs: -1
- objective: reg:squarederror
- eta: 0.075
- max_depth: 8
- min_child_weight: 5
- subsample: 1.0
- colsample_bytree: 1.0
- eval_metric: rmse
- explain_level: 1
Validation
- validation_type: kfold
- k_folds: 5
- shuffle: True
Optimized metric
rmse
Training time
4.3 seconds
Metric details:
| Metric |
Score |
| MAE |
109.035 |
| MSE |
20247.8 |
| RMSE |
142.295 |
| R2 |
0.736576 |
| MAPE |
0.169757 |
Learning curves
Permutation-based Importance
True vs Predicted
Predicted vs Residuals
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Summary of 5_Default_RandomForest
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Random Forest
- n_jobs: -1
- criterion: squared_error
- max_features: 0.9
- min_samples_split: 30
- max_depth: 4
- eval_metric_name: rmse
- explain_level: 1
Validation
- validation_type: kfold
- k_folds: 5
- shuffle: True
Optimized metric
rmse
Training time
90.7 seconds
Metric details:
| Metric |
Score |
| MAE |
129.944 |
| MSE |
27887.8 |
| RMSE |
166.996 |
| R2 |
0.63718 |
| MAPE |
0.190035 |
Learning curves
Permutation-based Importance
True vs Predicted
Predicted vs Residuals
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Summary of 1_Default_LightGBM
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LightGBM
- n_jobs: -1
- objective: regression
- num_leaves: 63
- learning_rate: 0.05
- feature_fraction: 0.9
- bagging_fraction: 0.9
- min_data_in_leaf: 10
- metric: rmse
- custom_eval_metric_name: None
- explain_level: 1
Validation
- validation_type: kfold
- k_folds: 5
- shuffle: True
Optimized metric
rmse
Training time
14.5 seconds
Metric details:
| Metric |
Score |
| MAE |
107.869 |
| MSE |
19896 |
| RMSE |
141.053 |
| R2 |
0.741153 |
| MAPE |
0.169065 |
Learning curves
Permutation-based Importance
True vs Predicted
Predicted vs Residuals
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